This files contains an example of tuning a multiple models with BayesSearchCV.

import pickle
import time

import helpsk as hlp
import pandas as pd
import numpy as np
import plotly.express as px
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler, MinMaxScaler, OneHotEncoder

import plotly.io as pio
pio.renderers.default='notebook'

Load Data

with open('../X_train.pkl', 'rb') as handle:
    X_train = pickle.load(handle)

with open('../y_train.pkl', 'rb') as handle:
    y_train = pickle.load(handle)

hlp.pandas.numeric_summary(X_train, return_style=True)

	# of Non-Nulls	# of Nulls	% Nulls	# of Zeros	% Zeros	Mean	St Dev.	Coef of Var	Skewness	Kurtosis	Min	10%	25%	50%	75%	90%	Max
duration	760	40	5.0%	0	0.0%	21.0	11.7	0.6	1.0	0.6	4.0	9.0	12.0	18.0	24.0	36.0	60.0
credit_amount	800	0	0.0%	38	5.0%	3,203.9	2,932.3	0.9	1.9	3.9	0.0	753.9	1,300.8	2,236.5	3,951.5	7,394.6	18,424.0
installment_commitment	800	0	0.0%	0	0.0%	3.0	1.1	0.4	-0.5	-1.2	1.0	1.0	2.0	3.0	4.0	4.0	4.0
residence_since	800	0	0.0%	0	0.0%	2.9	1.1	0.4	-0.3	-1.4	1.0	1.0	2.0	3.0	4.0	4.0	4.0
age	800	0	0.0%	0	0.0%	35.6	11.4	0.3	1.0	0.7	19.0	23.0	27.0	33.0	42.0	52.0	75.0
existing_credits	800	0	0.0%	0	0.0%	1.4	0.6	0.4	1.3	1.6	1.0	1.0	1.0	1.0	2.0	2.0	4.0
num_dependents	800	0	0.0%	0	0.0%	1.1	0.3	0.3	2.0	2.1	1.0	1.0	1.0	1.0	1.0	2.0	2.0

hlp.pandas.non_numeric_summary(X_train, return_style=True)

	# of Non-Nulls	# of Nulls	% Nulls	Most Freq. Value	# of Unique	% Unique
checking_status	763	37	4.6%	no checking	4	0.5%
credit_history	800	0	0.0%	existing paid	5	0.6%
purpose	800	0	0.0%	radio/tv	10	1.2%
savings_status	800	0	0.0%	<100	5	0.6%
employment	800	0	0.0%	1<=X<4	5	0.6%
personal_status	800	0	0.0%	male single	4	0.5%
other_parties	800	0	0.0%	none	3	0.4%
property_magnitude	800	0	0.0%	car	4	0.5%
other_payment_plans	800	0	0.0%	none	3	0.4%
housing	800	0	0.0%	own	3	0.4%
job	800	0	0.0%	skilled	4	0.5%
own_telephone	800	0	0.0%	none	2	0.2%
foreign_worker	800	0	0.0%	yes	2	0.2%

y_train[0:10]

array([1, 1, 0, 1, 0, 1, 0, 1, 1, 0])

np.unique(y_train, return_counts=True)

(array([0, 1]), array([559, 241]))

np.unique(y_train, return_counts=True)[1] / np.sum(np.unique(y_train, return_counts=True)[1])

array([0.69875, 0.30125])

skopt.BayesSearchCV

https://scikit-optimize.github.io/stable/auto_examples/sklearn-gridsearchcv-replacement.html

search_space = hlp.sklearn_search.BayesianSearchSpace(
    data=X_train,
    iterations=75,
    random_state=42,
)

# pip install scikit-optimize
from skopt import BayesSearchCV
from skopt.space import Real, Categorical, Integer
from sklearn.model_selection import RepeatedKFold

bayes_search = BayesSearchCV(
    estimator=search_space.pipeline(),
    search_spaces=search_space.search_spaces(),
    cv=RepeatedKFold(n_splits=5, n_repeats=2, random_state=42),  # 5 fold 2 repeat CV
    scoring='roc_auc',
    refit=False,  # required if passing in multiple scorers
    return_train_score=False,
    n_jobs=-1,
    verbose=1,
    random_state=42,
)

start_time = time.time()
bayes_search.fit(X_train, y_train)
elapsed_time = time.time() - start_time

print(f"Elapsed time to run BayesSearchCV: {elapsed_time:.3f} seconds; {elapsed_time / 60:.1f} minutes")

Elapsed time to run BayesSearchCV: 1378.075 seconds; 23.0 minutes

print(bayes_search.best_score_)

0.7786408178264201

print(bayes_search.best_params_)

OrderedDict([('model', RandomForestClassifier(n_estimators=500, random_state=42)), ('model__criterion', 'gini'), ('model__max_depth', 97), ('model__max_features', 0.05090164777078294), ('model__max_samples', 0.5133682135216073), ('model__min_samples_leaf', 2), ('model__min_samples_split', 24), ('model__n_estimators', 1544), ('prep__non_numeric__encoder__transformer', OneHotEncoder(handle_unknown='ignore')), ('prep__numeric__imputer__transformer', SimpleImputer(strategy='most_frequent')), ('prep__numeric__pca__transformer', None), ('prep__numeric__scaler__transformer', None)])

Results

results = hlp.sklearn_eval.MLExperimentResults.from_sklearn_search_cv(
    searcher=bayes_search,
    higher_score_is_better=True,
    description='BayesSearchCV using ClassifierSearchSpace',
    parameter_name_mappings=search_space.param_name_mappings()
)

results.to_yaml_file(yaml_file_name = 'Run 1 - Multi-model - BayesSearchCV.yaml')

results = hlp.sklearn_eval.MLExperimentResults.from_yaml_file(yaml_file_name = 'Run 1 - Multi-model - BayesSearchCV.yaml')

Best Scores/Params

results.best_score

0.7786408178264201

results.best_params

{'model': 'RandomForestClassifier()',
 'max_features': 0.05090164777078294,
 'max_depth': 97,
 'n_estimators': 1544,
 'min_samples_split': 24,
 'min_samples_leaf': 2,
 'max_samples': 0.5133682135216073,
 'criterion': 'gini',
 'imputer': "SimpleImputer(strategy='most_frequent')",
 'scaler': 'None',
 'pca': 'None',
 'encoder': 'OneHotEncoder()'}

df = results.to_formatted_dataframe(return_style=False, include_rank=True)
df["model_rank"] = df.groupby("model")["roc_auc Mean"].rank(method="first", ascending=False)
df.query('model_rank == 1')

	rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	model	C	max_features	max_depth	n_estimators	min_samples_split	...	subsample	colsample_bytree	colsample_bylevel	reg_alpha	reg_lambda	imputer	scaler	pca	encoder	model_rank
288	1	0.779	0.756	0.802	RandomForestClassifier()	NaN	0.050902	97.0	1544.0	24.0	...	NaN	NaN	NaN	NaN	NaN	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()	1.0
188	31	0.771	0.744	0.798	ExtraTreesClassifier()	NaN	0.010000	100.0	2000.0	50.0	...	NaN	NaN	NaN	NaN	NaN	SimpleImputer(strategy='median')	None	None	OneHotEncoder()	1.0
364	34	0.771	0.750	0.793	XGBClassifier()	NaN	NaN	20.0	500.0	NaN	...	0.691409	0.5	0.5	1.0	4.0	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()	1.0
73	38	0.771	0.751	0.791	LogisticRegression()	0.055044	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()	1.0
128	60	0.770	0.749	0.791	LinearSVC()	0.005470	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()	1.0

5 rows × 25 columns

results.to_formatted_dataframe(return_style=True,
                               include_rank=True,
                               num_rows=1000)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	model	C	max_features	max_depth	n_estimators	min_samples_split	min_samples_leaf	max_samples	criterion	learning_rate	min_child_weight	subsample	colsample_bytree	colsample_bylevel	reg_alpha	reg_lambda	imputer	scaler	pca	encoder
1	0.779	0.756	0.802	RandomForestClassifier()	<NA>	0.051	97.000	1,544.000	24.000	2.000	0.513	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
2	0.778	0.756	0.799	RandomForestClassifier()	<NA>	0.010	100.000	2,000.000	35.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
3	0.777	0.754	0.800	RandomForestClassifier()	<NA>	0.010	62.000	2,000.000	35.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
4	0.777	0.754	0.800	RandomForestClassifier()	<NA>	0.070	56.000	1,870.000	49.000	2.000	0.563	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
5	0.777	0.755	0.800	RandomForestClassifier()	<NA>	0.010	100.000	2,000.000	50.000	1.000	0.539	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
6	0.777	0.756	0.798	RandomForestClassifier()	<NA>	0.035	63.000	859.000	21.000	1.000	0.916	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
7	0.776	0.756	0.797	RandomForestClassifier()	<NA>	0.010	61.000	1,153.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
8	0.776	0.755	0.798	RandomForestClassifier()	<NA>	0.016	32.000	869.000	25.000	2.000	0.772	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
9	0.776	0.755	0.797	RandomForestClassifier()	<NA>	0.010	33.000	2,000.000	50.000	1.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
10	0.776	0.754	0.798	RandomForestClassifier()	<NA>	0.010	44.000	2,000.000	19.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
11	0.776	0.754	0.798	RandomForestClassifier()	<NA>	0.010	42.000	2,000.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
12	0.776	0.754	0.797	RandomForestClassifier()	<NA>	0.010	100.000	2,000.000	31.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
13	0.776	0.753	0.798	RandomForestClassifier()	<NA>	0.010	100.000	2,000.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
14	0.775	0.751	0.799	RandomForestClassifier()	<NA>	0.010	83.000	500.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
15	0.775	0.753	0.797	RandomForestClassifier()	<NA>	0.010	59.000	2,000.000	40.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
16	0.775	0.751	0.799	RandomForestClassifier()	<NA>	0.027	13.000	565.000	7.000	3.000	0.512	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
17	0.775	0.753	0.797	RandomForestClassifier()	<NA>	0.010	62.000	2,000.000	37.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
18	0.775	0.752	0.797	RandomForestClassifier()	<NA>	0.010	80.000	708.000	28.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
19	0.775	0.752	0.797	RandomForestClassifier()	<NA>	0.010	74.000	2,000.000	26.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
20	0.774	0.751	0.798	RandomForestClassifier()	<NA>	0.010	100.000	500.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
21	0.774	0.752	0.797	RandomForestClassifier()	<NA>	0.010	84.000	2,000.000	50.000	1.000	0.620	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
22	0.774	0.754	0.795	RandomForestClassifier()	<NA>	0.071	49.000	586.000	20.000	2.000	0.730	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
23	0.774	0.751	0.797	RandomForestClassifier()	<NA>	0.010	100.000	2,000.000	50.000	1.000	0.761	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
24	0.774	0.752	0.796	RandomForestClassifier()	<NA>	0.010	100.000	500.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
25	0.774	0.751	0.796	RandomForestClassifier()	<NA>	0.010	55.000	2,000.000	20.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
26	0.773	0.753	0.794	RandomForestClassifier()	<NA>	0.010	42.000	2,000.000	32.000	1.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
27	0.773	0.753	0.793	RandomForestClassifier()	<NA>	0.023	19.000	1,276.000	3.000	2.000	0.993	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
28	0.772	0.751	0.794	RandomForestClassifier()	<NA>	0.010	43.000	1,940.000	34.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
29	0.772	0.752	0.792	RandomForestClassifier()	<NA>	0.114	47.000	1,045.000	5.000	2.000	0.509	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
30	0.772	0.745	0.798	RandomForestClassifier()	<NA>	0.057	2.000	546.000	21.000	2.000	0.528	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
31	0.771	0.744	0.798	ExtraTreesClassifier()	<NA>	0.010	100.000	2,000.000	50.000	4.000	0.758	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
32	0.771	0.746	0.797	RandomForestClassifier()	<NA>	0.010	1.000	500.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
33	0.771	0.744	0.799	ExtraTreesClassifier()	<NA>	0.010	77.000	2,000.000	50.000	4.000	0.732	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
34	0.771	0.750	0.793	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.691	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
35	0.771	0.744	0.798	ExtraTreesClassifier()	<NA>	0.010	13.000	2,000.000	50.000	4.000	0.744	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
36	0.771	0.744	0.797	ExtraTreesClassifier()	<NA>	0.010	34.000	2,000.000	50.000	3.000	0.719	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
37	0.771	0.743	0.798	ExtraTreesClassifier()	<NA>	0.010	38.000	2,000.000	50.000	4.000	0.734	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
38	0.771	0.751	0.791	LogisticRegression()	0.055	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
39	0.771	0.750	0.791	LogisticRegression()	0.049	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
40	0.771	0.744	0.797	ExtraTreesClassifier()	<NA>	0.010	44.000	2,000.000	50.000	3.000	0.733	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
41	0.771	0.744	0.797	ExtraTreesClassifier()	<NA>	0.010	100.000	2,000.000	50.000	3.000	0.729	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
42	0.771	0.751	0.791	LogisticRegression()	0.062	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
43	0.771	0.743	0.798	ExtraTreesClassifier()	<NA>	0.010	13.000	2,000.000	50.000	4.000	0.729	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
44	0.771	0.748	0.794	XGBClassifier()	<NA>	<NA>	5.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
45	0.771	0.748	0.793	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
46	0.771	0.743	0.798	ExtraTreesClassifier()	<NA>	0.010	76.000	2,000.000	50.000	4.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
47	0.771	0.743	0.798	ExtraTreesClassifier()	<NA>	0.010	75.000	2,000.000	50.000	4.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
48	0.771	0.747	0.794	RandomForestClassifier()	<NA>	0.011	6.000	1,996.000	7.000	10.000	0.652	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
49	0.771	0.743	0.798	ExtraTreesClassifier()	<NA>	0.010	80.000	2,000.000	50.000	4.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
50	0.770	0.750	0.791	LogisticRegression()	0.077	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
51	0.770	0.750	0.791	LogisticRegression()	0.075	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
52	0.770	0.750	0.791	LogisticRegression()	0.075	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
53	0.770	0.750	0.791	LogisticRegression()	0.075	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
54	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
55	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
56	0.770	0.744	0.797	ExtraTreesClassifier()	<NA>	0.010	47.000	2,000.000	50.000	3.000	0.734	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
57	0.770	0.750	0.791	LogisticRegression()	0.075	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
58	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
59	0.770	0.748	0.793	XGBClassifier()	<NA>	<NA>	10.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
60	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
61	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
62	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
63	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
64	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
65	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
66	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
67	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
68	0.770	0.750	0.791	LogisticRegression()	0.089	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
69	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
70	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
71	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
72	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
73	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
74	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
75	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
76	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
77	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
78	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
79	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
80	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
81	0.770	0.749	0.791	LinearSVC()	0.007	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
82	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
83	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
84	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
85	0.770	0.750	0.791	LogisticRegression()	0.073	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
86	0.770	0.750	0.791	LogisticRegression()	0.073	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
87	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
88	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
89	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
90	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
91	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
92	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
93	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
94	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
95	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
96	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
97	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
98	0.770	0.750	0.791	LogisticRegression()	0.074	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
99	0.770	0.750	0.791	RandomForestClassifier()	<NA>	0.060	96.000	575.000	26.000	3.000	0.592	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
100	0.770	0.748	0.792	RandomForestClassifier()	<NA>	0.206	19.000	1,985.000	6.000	2.000	0.749	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
101	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
102	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
103	0.770	0.750	0.791	LogisticRegression()	0.087	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
104	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
105	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
106	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
107	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
108	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
109	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
110	0.770	0.747	0.793	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.505	0.849	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
111	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
112	0.770	0.749	0.791	RandomForestClassifier()	<NA>	0.040	95.000	1,003.000	33.000	15.000	0.947	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
113	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
114	0.770	0.749	0.791	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
115	0.770	0.750	0.790	LogisticRegression()	0.092	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
116	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
117	0.770	0.749	0.791	LinearSVC()	0.005	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
118	0.770	0.750	0.790	LogisticRegression()	0.067	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
119	0.770	0.748	0.791	XGBClassifier()	<NA>	<NA>	8.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.725	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
120	0.770	0.742	0.798	ExtraTreesClassifier()	<NA>	0.036	46.000	1,618.000	42.000	3.000	0.717	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
121	0.770	0.743	0.796	ExtraTreesClassifier()	<NA>	0.010	61.000	2,000.000	33.000	3.000	0.753	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
122	0.770	0.749	0.791	RandomForestClassifier()	<NA>	0.044	39.000	1,564.000	47.000	4.000	0.552	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
123	0.770	0.750	0.790	LinearSVC()	0.004	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
124	0.770	0.748	0.791	LinearSVC()	0.009	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
125	0.770	0.742	0.797	ExtraTreesClassifier()	<NA>	0.010	31.000	2,000.000	50.000	5.000	0.795	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
126	0.770	0.744	0.795	ExtraTreesClassifier()	<NA>	0.010	62.000	1,869.000	20.000	3.000	0.704	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
127	0.769	0.748	0.790	LinearSVC()	0.009	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
128	0.769	0.749	0.790	LogisticRegression()	0.121	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
129	0.769	0.749	0.789	LinearSVC()	0.004	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
130	0.769	0.742	0.797	ExtraTreesClassifier()	<NA>	0.010	81.000	2,000.000	50.000	5.000	0.779	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
131	0.769	0.740	0.798	ExtraTreesClassifier()	<NA>	0.010	100.000	2,000.000	50.000	7.000	0.908	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
132	0.769	0.746	0.792	XGBClassifier()	<NA>	<NA>	4.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
133	0.769	0.747	0.791	XGBClassifier()	<NA>	<NA>	13.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
134	0.769	0.748	0.790	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.766	0.511	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
135	0.769	0.746	0.792	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.755	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
136	0.769	0.748	0.790	LinearSVC()	0.008	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
137	0.769	0.749	0.789	LogisticRegression()	0.097	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
138	0.769	0.747	0.791	RandomForestClassifier()	<NA>	0.270	80.000	576.000	44.000	2.000	0.882	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
139	0.768	0.743	0.793	ExtraTreesClassifier()	<NA>	0.010	10.000	2,000.000	50.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
140	0.768	0.746	0.790	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.500	0.604	0.617	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
141	0.768	0.742	0.794	RandomForestClassifier()	<NA>	0.010	1.000	1,398.000	33.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
142	0.768	0.741	0.795	ExtraTreesClassifier()	<NA>	0.070	40.000	1,169.000	44.000	1.000	0.684	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
143	0.768	0.748	0.788	LinearSVC()	0.011	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
144	0.768	0.748	0.788	LogisticRegression()	0.132	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	None	OneHotEncoder()
145	0.768	0.747	0.789	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.767	0.500	0.769	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
146	0.768	0.743	0.792	ExtraTreesClassifier()	<NA>	0.010	96.000	2,000.000	50.000	1.000	0.851	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
147	0.768	0.746	0.790	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	1.000	0.137	3.234	SimpleImputer()	None	None	OneHotEncoder()
148	0.767	0.743	0.792	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.672	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
149	0.767	0.747	0.788	XGBClassifier()	<NA>	<NA>	1.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.500	0.500	0.500	0.120	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
150	0.767	0.746	0.788	RandomForestClassifier()	<NA>	0.016	97.000	540.000	43.000	2.000	0.979	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
151	0.766	0.737	0.796	ExtraTreesClassifier()	<NA>	0.010	3.000	2,000.000	50.000	3.000	0.716	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
152	0.766	0.745	0.787	LinearSVC()	0.018	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
153	0.766	0.743	0.790	RandomForestClassifier()	<NA>	0.350	77.000	1,998.000	18.000	1.000	0.992	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
154	0.766	0.743	0.790	RandomForestClassifier()	<NA>	0.042	70.000	1,849.000	49.000	22.000	0.672	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
155	0.766	0.740	0.793	ExtraTreesClassifier()	<NA>	0.021	17.000	1,773.000	38.000	2.000	0.925	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
156	0.766	0.744	0.788	ExtraTreesClassifier()	<NA>	0.023	57.000	1,928.000	8.000	1.000	0.514	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
157	0.766	0.745	0.786	XGBClassifier()	<NA>	<NA>	2.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
158	0.766	0.737	0.794	ExtraTreesClassifier()	<NA>	0.010	32.000	2,000.000	37.000	12.000	0.743	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
159	0.765	0.742	0.789	RandomForestClassifier()	<NA>	0.080	11.000	1,950.000	50.000	15.000	0.838	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
160	0.765	0.746	0.784	RandomForestClassifier()	<NA>	0.094	89.000	865.000	50.000	5.000	0.555	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
161	0.765	0.747	0.783	RandomForestClassifier()	<NA>	0.016	95.000	1,900.000	23.000	7.000	0.667	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
162	0.765	0.743	0.787	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	1.000	1.000	1.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
163	0.765	0.733	0.797	ExtraTreesClassifier()	<NA>	0.010	1.000	1,379.000	50.000	7.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
164	0.765	0.735	0.795	ExtraTreesClassifier()	<NA>	0.105	84.000	692.000	32.000	1.000	0.639	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
165	0.765	0.738	0.791	ExtraTreesClassifier()	<NA>	0.010	100.000	500.000	50.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
166	0.765	0.738	0.791	RandomForestClassifier()	<NA>	0.017	2.000	1,934.000	4.000	1.000	0.756	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
167	0.764	0.742	0.787	RandomForestClassifier()	<NA>	0.032	100.000	1,028.000	23.000	31.000	0.586	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
168	0.764	0.734	0.795	LogisticRegression()	0.054	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
169	0.764	0.734	0.794	LinearSVC()	0.006	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
170	0.764	0.745	0.783	ExtraTreesClassifier()	<NA>	0.017	7.000	1,885.000	6.000	5.000	0.951	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
171	0.764	0.743	0.785	LinearSVC()	0.002	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
172	0.764	0.742	0.787	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.500	1.000	0.553	0.203	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
173	0.764	0.733	0.796	ExtraTreesClassifier()	<NA>	0.010	1.000	2,000.000	50.000	8.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
174	0.764	0.734	0.794	LinearSVC()	0.011	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
175	0.764	0.735	0.793	LogisticRegression()	0.125	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
176	0.763	0.743	0.783	XGBClassifier()	<NA>	<NA>	10.000	1,216.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
177	0.763	0.745	0.781	ExtraTreesClassifier()	<NA>	0.010	100.000	2,000.000	50.000	4.000	0.787	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
178	0.763	0.736	0.790	LogisticRegression()	0.281	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
179	0.763	0.740	0.786	XGBClassifier()	<NA>	<NA>	20.000	530.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.500	0.770	0.563	0.414	1.793	SimpleImputer()	None	None	CustomOrdinalEncoder()
180	0.763	0.735	0.791	ExtraTreesClassifier()	<NA>	0.051	83.000	1,727.000	22.000	11.000	0.977	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
181	0.763	0.733	0.793	LogisticRegression()	0.031	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
182	0.763	0.743	0.783	RandomForestClassifier()	<NA>	0.010	100.000	2,000.000	2.000	1.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
183	0.763	0.748	0.778	ExtraTreesClassifier()	<NA>	0.010	77.000	2,000.000	2.000	1.000	0.870	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
184	0.763	0.741	0.785	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.741	0.500	0.500	0.000	4.000	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
185	0.763	0.743	0.783	XGBClassifier()	<NA>	<NA>	10.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.720	1.000	0.576	1.000	3.797	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
186	0.762	0.741	0.784	XGBClassifier()	<NA>	<NA>	11.000	536.000	<NA>	<NA>	<NA>	<NA>	0.013	2.000	0.661	0.525	0.683	0.063	2.415	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
187	0.762	0.741	0.783	RandomForestClassifier()	<NA>	0.488	35.000	1,033.000	32.000	8.000	0.613	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
188	0.762	0.741	0.784	ExtraTreesClassifier()	<NA>	0.025	18.000	800.000	39.000	4.000	0.532	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
189	0.762	0.732	0.792	ExtraTreesClassifier()	<NA>	0.010	1.000	1,707.000	2.000	1.000	0.599	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
190	0.762	0.732	0.792	LogisticRegression()	0.023	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
191	0.762	0.737	0.787	LinearSVC()	0.059	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
192	0.761	0.738	0.785	RandomForestClassifier()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
193	0.761	0.736	0.787	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.796	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
194	0.761	0.745	0.778	ExtraTreesClassifier()	<NA>	0.010	100.000	500.000	2.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
195	0.761	0.740	0.781	RandomForestClassifier()	<NA>	0.025	3.000	1,534.000	3.000	45.000	0.928	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
196	0.761	0.732	0.789	ExtraTreesClassifier()	<NA>	0.058	12.000	533.000	37.000	13.000	0.993	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
197	0.761	0.740	0.781	LinearSVC()	0.089	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
198	0.761	0.737	0.785	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	1.000	0.747	0.000	1.000	SimpleImputer()	None	None	OneHotEncoder()
199	0.760	0.730	0.790	LogisticRegression()	0.012	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
200	0.760	0.734	0.786	ExtraTreesClassifier()	<NA>	0.950	71.000	640.000	50.000	1.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
201	0.759	0.741	0.778	RandomForestClassifier()	<NA>	0.030	11.000	663.000	49.000	49.000	0.606	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
202	0.759	0.736	0.782	RandomForestClassifier()	<NA>	0.947	13.000	1,822.000	50.000	2.000	0.857	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
203	0.759	0.735	0.784	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.762	1.000	0.000	1.000	SimpleImputer()	None	None	CustomOrdinalEncoder()
204	0.759	0.734	0.785	RandomForestClassifier()	<NA>	0.879	40.000	1,540.000	19.000	1.000	0.501	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
205	0.759	0.739	0.779	RandomForestClassifier()	<NA>	0.098	94.000	804.000	40.000	46.000	0.945	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
206	0.759	0.735	0.783	RandomForestClassifier()	<NA>	0.595	94.000	1,235.000	6.000	2.000	0.611	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
207	0.759	0.737	0.781	LinearSVC()	0.140	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
208	0.758	0.736	0.781	LogisticRegression()	0.897	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
209	0.758	0.738	0.779	RandomForestClassifier()	<NA>	0.025	20.000	945.000	30.000	49.000	0.523	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
210	0.758	0.747	0.770	ExtraTreesClassifier()	<NA>	0.010	49.000	2,000.000	2.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
211	0.758	0.733	0.784	ExtraTreesClassifier()	<NA>	0.915	89.000	1,892.000	34.000	1.000	0.737	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
212	0.758	0.736	0.780	RandomForestClassifier()	<NA>	0.826	93.000	1,047.000	49.000	5.000	0.918	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
213	0.758	0.735	0.781	LogisticRegression()	0.007	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
214	0.758	0.733	0.782	ExtraTreesClassifier()	<NA>	0.307	54.000	691.000	12.000	6.000	0.898	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
215	0.758	0.734	0.781	ExtraTreesClassifier()	<NA>	0.506	57.000	1,593.000	44.000	3.000	0.748	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
216	0.758	0.739	0.777	LogisticRegression()	1.209	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
217	0.757	0.732	0.783	ExtraTreesClassifier()	<NA>	0.505	87.000	1,944.000	34.000	8.000	0.522	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
218	0.757	0.738	0.777	LogisticRegression()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
219	0.757	0.747	0.768	ExtraTreesClassifier()	<NA>	0.010	79.000	500.000	2.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
220	0.757	0.732	0.782	ExtraTreesClassifier()	<NA>	0.505	94.000	1,899.000	44.000	6.000	0.905	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
221	0.757	0.734	0.780	XGBClassifier()	<NA>	<NA>	3.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.795	0.578	0.641	1.000	1.528	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
222	0.757	0.735	0.779	XGBClassifier()	<NA>	<NA>	1.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.778	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
223	0.757	0.735	0.779	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	4.000	0.500	0.952	0.695	1.000	4.000	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
224	0.757	0.738	0.776	LinearSVC()	0.237	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
225	0.757	0.733	0.780	ExtraTreesClassifier()	<NA>	0.560	11.000	1,663.000	42.000	7.000	0.998	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
226	0.757	0.736	0.777	XGBClassifier()	<NA>	<NA>	1.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	6.000	0.640	0.500	0.500	0.003	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
227	0.756	0.734	0.778	RandomForestClassifier()	<NA>	0.010	100.000	500.000	2.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
228	0.756	0.727	0.784	LogisticRegression()	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	None	OneHotEncoder()
229	0.755	0.730	0.781	RandomForestClassifier()	<NA>	0.592	21.000	1,165.000	48.000	1.000	0.552	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
230	0.755	0.727	0.784	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
231	0.755	0.727	0.784	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
232	0.755	0.727	0.784	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
233	0.755	0.727	0.784	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
234	0.755	0.730	0.779	XGBClassifier()	<NA>	<NA>	1.000	779.000	<NA>	<NA>	<NA>	<NA>	0.010	3.000	0.500	0.874	0.509	0.003	2.278	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
235	0.755	0.738	0.771	ExtraTreesClassifier()	<NA>	0.018	100.000	686.000	30.000	12.000	0.831	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
236	0.755	0.731	0.778	ExtraTreesClassifier()	<NA>	0.738	45.000	606.000	6.000	15.000	0.995	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
237	0.755	0.733	0.776	RandomForestClassifier()	<NA>	0.058	24.000	1,363.000	7.000	24.000	0.631	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
238	0.755	0.732	0.777	XGBClassifier()	<NA>	<NA>	2.000	660.000	<NA>	<NA>	<NA>	<NA>	0.010	8.000	0.677	0.501	0.926	0.000	1.037	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
239	0.754	0.726	0.783	LinearSVC()	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
240	0.754	0.728	0.781	ExtraTreesClassifier()	<NA>	0.058	40.000	1,962.000	45.000	40.000	0.982	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
241	0.754	0.736	0.772	RandomForestClassifier()	<NA>	0.035	85.000	791.000	9.000	48.000	0.502	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
242	0.754	0.730	0.778	ExtraTreesClassifier()	<NA>	0.760	100.000	1,678.000	2.000	1.000	0.578	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
243	0.754	0.726	0.781	ExtraTreesClassifier()	<NA>	0.941	72.000	906.000	24.000	1.000	0.953	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
244	0.754	0.728	0.779	RandomForestClassifier()	<NA>	0.950	87.000	1,550.000	41.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
245	0.753	0.733	0.774	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
246	0.753	0.726	0.779	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.500	1.000	0.000	1.000	SimpleImputer()	None	None	OneHotEncoder()
247	0.752	0.726	0.778	ExtraTreesClassifier()	<NA>	0.946	7.000	885.000	48.000	13.000	0.523	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
248	0.752	0.721	0.782	ExtraTreesClassifier()	<NA>	0.031	73.000	1,752.000	24.000	32.000	0.983	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
249	0.752	0.728	0.775	ExtraTreesClassifier()	<NA>	0.950	51.000	2,000.000	50.000	8.000	0.624	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
250	0.752	0.727	0.777	LinearSVC()	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
251	0.752	0.723	0.780	LinearSVC()	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
252	0.751	0.725	0.778	ExtraTreesClassifier()	<NA>	0.013	49.000	518.000	22.000	36.000	0.512	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
253	0.751	0.729	0.774	RandomForestClassifier()	<NA>	0.936	83.000	665.000	50.000	7.000	0.516	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
254	0.751	0.727	0.775	RandomForestClassifier()	<NA>	0.849	13.000	607.000	2.000	5.000	0.969	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
255	0.751	0.729	0.772	XGBClassifier()	<NA>	<NA>	1.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	1.000	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
256	0.751	0.727	0.774	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	8.000	0.650	0.805	0.500	1.000	1.150	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
257	0.751	0.732	0.769	LogisticRegression()	4.732	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
258	0.750	0.729	0.772	XGBClassifier()	<NA>	<NA>	5.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	12.000	0.755	0.500	0.817	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
259	0.750	0.719	0.781	ExtraTreesClassifier()	<NA>	0.029	1.000	1,721.000	7.000	19.000	0.666	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
260	0.750	0.732	0.768	LinearSVC()	3.171	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
261	0.750	0.733	0.767	ExtraTreesClassifier()	<NA>	0.051	2.000	576.000	19.000	13.000	0.974	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
262	0.749	0.732	0.767	LinearSVC()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
263	0.749	0.733	0.766	RandomForestClassifier()	<NA>	0.031	48.000	1,751.000	48.000	48.000	0.979	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
264	0.749	0.731	0.768	LinearSVC()	2.341	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
265	0.749	0.726	0.772	RandomForestClassifier()	<NA>	0.293	100.000	878.000	42.000	38.000	0.532	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
266	0.749	0.729	0.769	RandomForestClassifier()	<NA>	0.265	17.000	650.000	25.000	22.000	0.547	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
267	0.749	0.729	0.769	ExtraTreesClassifier()	<NA>	0.010	100.000	2,000.000	2.000	13.000	0.500	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
268	0.749	0.723	0.774	ExtraTreesClassifier()	<NA>	0.937	95.000	1,941.000	49.000	20.000	0.730	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
269	0.748	0.724	0.773	ExtraTreesClassifier()	<NA>	0.201	65.000	565.000	27.000	24.000	0.987	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
270	0.748	0.730	0.766	LinearSVC()	4.448	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
271	0.748	0.719	0.778	ExtraTreesClassifier()	<NA>	0.010	1.000	2,000.000	2.000	50.000	1.000	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
272	0.748	0.727	0.769	XGBClassifier()	<NA>	<NA>	20.000	515.000	<NA>	<NA>	<NA>	<NA>	0.010	15.000	0.702	1.000	1.000	1.000	1.000	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
273	0.747	0.730	0.764	LinearSVC()	1.907	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
274	0.747	0.723	0.772	XGBClassifier()	<NA>	<NA>	20.000	582.000	<NA>	<NA>	<NA>	<NA>	0.016	3.000	0.500	0.903	0.505	0.000	1.061	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
275	0.747	0.725	0.768	XGBClassifier()	<NA>	<NA>	20.000	1,434.000	<NA>	<NA>	<NA>	<NA>	0.012	1.000	0.746	0.842	0.656	0.000	2.214	SimpleImputer()	None	None	OneHotEncoder()
276	0.747	0.723	0.771	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.500	0.579	0.562	1.000	2.486	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
277	0.747	0.721	0.772	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	24.000	1.000	0.880	0.500	1.000	1.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
278	0.747	0.728	0.765	RandomForestClassifier()	<NA>	0.060	99.000	1,612.000	7.000	50.000	0.820	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
279	0.746	0.722	0.770	ExtraTreesClassifier()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
280	0.746	0.726	0.767	XGBClassifier()	<NA>	<NA>	5.000	1,130.000	<NA>	<NA>	<NA>	<NA>	0.014	7.000	0.513	0.885	0.899	0.360	1.495	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
281	0.745	0.727	0.762	LogisticRegression()	98.285	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
282	0.745	0.728	0.762	LogisticRegression()	23.327	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	None	OneHotEncoder()
283	0.745	0.726	0.763	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	3.000	0.500	0.500	1.000	1.000	4.000	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
284	0.744	0.721	0.767	ExtraTreesClassifier()	<NA>	0.031	37.000	589.000	25.000	50.000	0.527	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
285	0.744	0.726	0.762	LogisticRegression()	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
286	0.744	0.723	0.765	XGBClassifier()	<NA>	<NA>	1.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.040	12.000	1.000	0.500	0.833	0.633	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
287	0.744	0.723	0.764	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	10.000	0.525	0.500	1.000	0.102	4.000	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
288	0.743	0.722	0.764	RandomForestClassifier()	<NA>	0.667	21.000	1,313.000	38.000	28.000	0.745	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
289	0.743	0.717	0.769	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.753	0.605	0.501	1.000	1.993	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
290	0.742	0.718	0.765	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.984	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
291	0.741	0.719	0.763	ExtraTreesClassifier()	<NA>	0.950	100.000	967.000	2.000	17.000	0.500	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
292	0.741	0.718	0.763	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	0.856	1.000	1.000	1.000	1.648	SimpleImputer()	None	None	OneHotEncoder()
293	0.741	0.715	0.766	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	3.000	0.831	0.519	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
294	0.740	0.719	0.761	ExtraTreesClassifier()	<NA>	0.011	4.000	671.000	39.000	29.000	0.501	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
295	0.740	0.721	0.760	ExtraTreesClassifier()	<NA>	0.402	81.000	732.000	24.000	31.000	0.997	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
296	0.740	0.718	0.762	ExtraTreesClassifier()	<NA>	0.729	16.000	716.000	34.000	26.000	0.998	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
297	0.740	0.717	0.763	RandomForestClassifier()	<NA>	0.543	40.000	732.000	40.000	37.000	0.637	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
298	0.740	0.720	0.759	ExtraTreesClassifier()	<NA>	0.669	17.000	1,860.000	28.000	35.000	0.601	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
299	0.739	0.719	0.759	RandomForestClassifier()	<NA>	0.840	5.000	880.000	24.000	34.000	0.541	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
300	0.739	0.714	0.764	ExtraTreesClassifier()	<NA>	0.763	81.000	656.000	48.000	29.000	0.907	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
301	0.739	0.719	0.759	XGBClassifier()	<NA>	<NA>	20.000	599.000	<NA>	<NA>	<NA>	<NA>	0.011	1.000	1.000	1.000	0.838	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
302	0.738	0.717	0.759	RandomForestClassifier()	<NA>	0.560	74.000	1,544.000	14.000	42.000	0.603	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
303	0.738	0.715	0.762	XGBClassifier()	<NA>	<NA>	10.000	1,519.000	<NA>	<NA>	<NA>	<NA>	0.018	11.000	0.527	0.546	0.947	0.000	2.109	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
304	0.738	0.718	0.758	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	0.826	1.000	1.000	0.000	3.104	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
305	0.737	0.712	0.761	RandomForestClassifier()	<NA>	0.851	1.000	844.000	3.000	6.000	0.504	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
306	0.736	0.707	0.765	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	20.000	1.000	1.000	0.639	0.003	4.000	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
307	0.735	0.706	0.765	LogisticRegression()	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
308	0.735	0.710	0.759	RandomForestClassifier()	<NA>	0.861	99.000	1,556.000	13.000	27.000	0.699	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
309	0.734	0.712	0.757	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	6.000	0.892	1.000	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
310	0.734	0.714	0.754	XGBClassifier()	<NA>	<NA>	20.000	1,005.000	<NA>	<NA>	<NA>	<NA>	0.010	2.000	1.000	0.801	0.682	0.208	1.000	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
311	0.734	0.713	0.755	ExtraTreesClassifier()	<NA>	0.894	58.000	1,210.000	11.000	40.000	0.994	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
312	0.733	0.711	0.756	ExtraTreesClassifier()	<NA>	0.920	27.000	709.000	44.000	50.000	0.576	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
313	0.733	0.711	0.755	XGBClassifier()	<NA>	<NA>	10.000	1,267.000	<NA>	<NA>	<NA>	<NA>	0.022	33.000	0.985	0.644	0.850	0.864	3.999	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
314	0.731	0.713	0.750	LogisticRegression()	0.027	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
315	0.731	0.715	0.747	RandomForestClassifier()	<NA>	0.826	100.000	1,076.000	42.000	50.000	0.698	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
316	0.731	0.712	0.750	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
317	0.731	0.716	0.746	RandomForestClassifier()	<NA>	0.916	56.000	655.000	2.000	49.000	0.553	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	OneHotEncoder()
318	0.731	0.706	0.756	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	1.000	1.000	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
319	0.731	0.715	0.747	ExtraTreesClassifier()	<NA>	0.020	69.000	1,709.000	23.000	49.000	0.929	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
320	0.731	0.712	0.749	LogisticRegression()	0.004	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
321	0.731	0.709	0.752	ExtraTreesClassifier()	<NA>	0.812	5.000	1,864.000	44.000	46.000	0.912	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
322	0.730	0.699	0.761	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
323	0.729	0.710	0.748	LinearSVC()	0.003	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
324	0.729	0.698	0.760	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
325	0.729	0.704	0.753	ExtraTreesClassifier()	<NA>	0.950	1.000	500.000	2.000	1.000	1.000	gini	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	CustomOrdinalEncoder()
326	0.729	0.705	0.752	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.010	50.000	1.000	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	None	CustomOrdinalEncoder()
327	0.728	0.697	0.760	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
328	0.728	0.707	0.749	XGBClassifier()	<NA>	<NA>	20.000	1,208.000	<NA>	<NA>	<NA>	<NA>	0.300	1.000	0.879	1.000	1.000	1.000	2.751	SimpleImputer(strategy='most_frequent')	None	None	OneHotEncoder()
329	0.728	0.706	0.750	XGBClassifier()	<NA>	<NA>	20.000	1,411.000	<NA>	<NA>	<NA>	<NA>	0.012	1.000	1.000	0.500	0.545	0.000	2.614	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
330	0.728	0.697	0.759	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
331	0.728	0.706	0.750	ExtraTreesClassifier()	<NA>	0.894	24.000	798.000	31.000	41.000	0.517	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
332	0.728	0.710	0.746	LogisticRegression()	0.251	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	CustomOrdinalEncoder()
333	0.727	0.703	0.751	XGBClassifier()	<NA>	<NA>	20.000	2,000.000	<NA>	<NA>	<NA>	<NA>	0.020	1.000	0.617	0.948	0.883	0.000	2.928	SimpleImputer(strategy='most_frequent')	None	PCA('mle')	CustomOrdinalEncoder()
334	0.727	0.710	0.744	LinearSVC()	0.030	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
335	0.726	0.707	0.745	LinearSVC()	0.377	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	CustomOrdinalEncoder()
336	0.726	0.704	0.747	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	None	CustomOrdinalEncoder()
337	0.725	0.706	0.744	LinearSVC()	0.718	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
338	0.725	0.707	0.743	LogisticRegression()	88.004	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	CustomOrdinalEncoder()
339	0.725	0.707	0.743	LogisticRegression()	98.262	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	CustomOrdinalEncoder()
340	0.725	0.709	0.741	LogisticRegression()	3.489	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
341	0.725	0.700	0.749	XGBClassifier()	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	None	OneHotEncoder()
342	0.724	0.707	0.740	LogisticRegression()	10.021	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
343	0.723	0.705	0.742	LinearSVC()	0.028	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
344	0.723	0.702	0.745	XGBClassifier()	<NA>	<NA>	8.000	862.000	<NA>	<NA>	<NA>	<NA>	0.046	4.000	0.758	0.936	0.930	0.437	1.861	SimpleImputer()	None	None	OneHotEncoder()
345	0.723	0.704	0.742	LogisticRegression()	0.361	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
346	0.722	0.705	0.740	ExtraTreesClassifier()	<NA>	0.019	73.000	1,164.000	4.000	43.000	0.502	entropy	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
347	0.722	0.700	0.745	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
348	0.722	0.700	0.744	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
349	0.722	0.705	0.738	LinearSVC()	4.575	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
350	0.722	0.694	0.749	LinearSVC()	100.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
351	0.719	0.699	0.739	XGBClassifier()	<NA>	<NA>	20.000	500.000	<NA>	<NA>	<NA>	<NA>	0.300	50.000	1.000	0.642	0.738	0.000	3.218	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
352	0.717	0.696	0.738	XGBClassifier()	<NA>	<NA>	9.000	1,581.000	<NA>	<NA>	<NA>	<NA>	0.052	8.000	0.985	0.913	0.626	0.013	1.419	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
353	0.717	0.689	0.745	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
354	0.711	0.689	0.734	LogisticRegression()	0.019	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
355	0.709	0.685	0.733	LinearSVC()	0.002	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
356	0.709	0.680	0.737	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
357	0.707	0.685	0.729	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
358	0.707	0.681	0.733	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
359	0.706	0.680	0.733	XGBClassifier()	<NA>	<NA>	2.000	1,866.000	<NA>	<NA>	<NA>	<NA>	0.064	15.000	0.546	0.796	0.885	0.034	2.370	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
360	0.706	0.690	0.723	XGBClassifier()	<NA>	<NA>	17.000	1,332.000	<NA>	<NA>	<NA>	<NA>	0.298	1.000	0.507	0.790	0.512	0.003	1.642	SimpleImputer()	None	PCA('mle')	OneHotEncoder()
361	0.706	0.684	0.728	XGBClassifier()	<NA>	<NA>	2.000	1,352.000	<NA>	<NA>	<NA>	<NA>	0.067	10.000	0.952	0.516	0.591	0.061	1.080	SimpleImputer(strategy='median')	None	PCA('mle')	CustomOrdinalEncoder()
362	0.706	0.684	0.727	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
363	0.705	0.681	0.729	LinearSVC()	8.350	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
364	0.705	0.682	0.728	LogisticRegression()	0.001	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	None	CustomOrdinalEncoder()
365	0.703	0.680	0.726	XGBClassifier()	<NA>	<NA>	15.000	1,670.000	<NA>	<NA>	<NA>	<NA>	0.209	17.000	0.637	0.984	0.537	0.000	2.331	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
366	0.701	0.675	0.727	XGBClassifier()	<NA>	<NA>	3.000	1,618.000	<NA>	<NA>	<NA>	<NA>	0.132	3.000	0.691	0.993	0.911	0.054	1.880	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()
367	0.700	0.666	0.735	LinearSVC()	76.004	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
368	0.699	0.675	0.724	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
369	0.699	0.675	0.724	LogisticRegression()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	CustomOrdinalEncoder()
370	0.695	0.669	0.721	XGBClassifier()	<NA>	<NA>	1.000	500.000	<NA>	<NA>	<NA>	<NA>	0.010	50.000	1.000	1.000	0.789	0.020	2.377	SimpleImputer(strategy='median')	None	None	OneHotEncoder()
371	0.693	0.670	0.716	XGBClassifier()	<NA>	<NA>	9.000	1,131.000	<NA>	<NA>	<NA>	<NA>	0.258	6.000	0.911	0.921	0.826	0.003	2.131	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
372	0.685	0.665	0.706	XGBClassifier()	<NA>	<NA>	1.000	1,705.000	<NA>	<NA>	<NA>	<NA>	0.233	28.000	0.849	0.616	0.603	0.000	1.856	SimpleImputer()	None	PCA('mle')	CustomOrdinalEncoder()
373	0.685	0.660	0.710	XGBClassifier()	<NA>	<NA>	15.000	868.000	<NA>	<NA>	<NA>	<NA>	0.010	26.000	0.516	0.850	0.976	0.535	1.698	SimpleImputer(strategy='median')	None	PCA('mle')	OneHotEncoder()
374	0.679	0.652	0.706	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
375	0.674	0.651	0.696	LinearSVC()	96.749	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
376	0.671	0.648	0.694	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	CustomOrdinalEncoder()
377	0.669	0.617	0.721	LinearSVC()	97.043	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	CustomOrdinalEncoder()
378	0.664	0.642	0.687	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
379	0.650	0.623	0.676	LinearSVC()	0.000	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
380	0.500	<NA>	<NA>	XGBClassifier()	<NA>	<NA>	20.000	1,914.000	<NA>	<NA>	<NA>	<NA>	0.028	50.000	0.500	0.731	0.626	0.001	1.956	SimpleImputer(strategy='median')	None	None	CustomOrdinalEncoder()

results.to_formatted_dataframe(query='model == "LinearSVC()"', include_rank=True)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	C	imputer	scaler	pca	encoder
1	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
2	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
3	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
4	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
5	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
6	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
7	0.770	0.749	0.791	0.007	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
8	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
9	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
10	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
11	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
12	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
13	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
14	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
15	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
16	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
17	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
18	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
19	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
20	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
21	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
22	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
23	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
24	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
25	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
26	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
27	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
28	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
29	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
30	0.770	0.749	0.791	0.006	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
31	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
32	0.770	0.749	0.791	0.005	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
33	0.770	0.750	0.790	0.004	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
34	0.770	0.748	0.791	0.009	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
35	0.769	0.748	0.790	0.009	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
36	0.769	0.749	0.789	0.004	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
37	0.769	0.748	0.790	0.008	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
38	0.768	0.748	0.788	0.011	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
39	0.766	0.745	0.787	0.018	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
40	0.764	0.734	0.794	0.006	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
41	0.764	0.743	0.785	0.002	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
42	0.764	0.734	0.794	0.011	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
43	0.762	0.737	0.787	0.059	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
44	0.761	0.740	0.781	0.089	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
45	0.759	0.737	0.781	0.140	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
46	0.757	0.738	0.776	0.237	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
47	0.754	0.726	0.783	0.001	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
48	0.752	0.727	0.777	0.001	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
49	0.752	0.723	0.780	0.001	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
50	0.750	0.732	0.768	3.171	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
51	0.749	0.732	0.767	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
52	0.749	0.731	0.768	2.341	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
53	0.748	0.730	0.766	4.448	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
54	0.747	0.730	0.764	1.907	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
55	0.731	0.712	0.750	0.000	SimpleImputer()	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
56	0.729	0.710	0.748	0.003	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
57	0.727	0.710	0.744	0.030	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
58	0.726	0.707	0.745	0.377	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	CustomOrdinalEncoder()
59	0.725	0.706	0.744	0.718	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
60	0.723	0.705	0.742	0.028	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
61	0.722	0.705	0.738	4.575	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
62	0.722	0.694	0.749	100.000	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
63	0.717	0.689	0.745	0.000	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
64	0.709	0.685	0.733	0.002	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
65	0.709	0.680	0.737	0.000	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
66	0.707	0.685	0.729	0.000	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
67	0.707	0.681	0.733	0.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
68	0.706	0.684	0.727	0.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
69	0.705	0.681	0.729	8.350	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
70	0.700	0.666	0.735	76.004	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
71	0.679	0.652	0.706	0.000	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
72	0.674	0.651	0.696	96.749	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
73	0.671	0.648	0.694	0.000	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	CustomOrdinalEncoder()
74	0.669	0.617	0.721	97.043	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	CustomOrdinalEncoder()
75	0.664	0.642	0.687	0.000	SimpleImputer()	MinMaxScaler()	PCA('mle')	CustomOrdinalEncoder()
76	0.650	0.623	0.676	0.000	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()

results.to_formatted_dataframe(query='model == "XGBClassifier()"', include_rank=True)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	max_depth	n_estimators	learning_rate	min_child_weight	subsample	colsample_bytree	colsample_bylevel	reg_alpha	reg_lambda	imputer	pca	encoder
1	0.771	0.750	0.793	20.000	500.000	0.010	1.000	0.691	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
2	0.771	0.748	0.794	5.000	500.000	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
3	0.771	0.748	0.793	20.000	500.000	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
4	0.770	0.748	0.793	10.000	500.000	0.010	1.000	0.500	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
5	0.770	0.747	0.793	20.000	500.000	0.010	1.000	0.500	0.505	0.849	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
6	0.770	0.748	0.791	8.000	500.000	0.010	1.000	0.725	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
7	0.769	0.746	0.792	4.000	500.000	0.010	2.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
8	0.769	0.747	0.791	13.000	500.000	0.010	1.000	0.500	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
9	0.769	0.748	0.790	20.000	500.000	0.010	2.000	0.766	0.511	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
10	0.769	0.746	0.792	20.000	500.000	0.010	1.000	0.755	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
11	0.768	0.746	0.790	20.000	500.000	0.010	2.000	0.500	0.604	0.617	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
12	0.768	0.747	0.789	20.000	500.000	0.010	1.000	0.767	0.500	0.769	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
13	0.768	0.746	0.790	20.000	500.000	0.010	1.000	0.500	0.500	1.000	0.137	3.234	SimpleImputer()	None	OneHotEncoder()
14	0.767	0.743	0.792	20.000	500.000	0.010	1.000	0.672	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	CustomOrdinalEncoder()
15	0.767	0.747	0.788	1.000	2,000.000	0.010	2.000	0.500	0.500	0.500	0.120	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
16	0.766	0.745	0.786	2.000	2,000.000	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
17	0.765	0.743	0.787	20.000	500.000	0.010	1.000	0.500	0.500	1.000	1.000	1.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
18	0.764	0.742	0.787	20.000	500.000	0.010	2.000	0.500	1.000	0.553	0.203	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
19	0.763	0.743	0.783	10.000	1,216.000	0.010	1.000	0.500	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
20	0.763	0.740	0.786	20.000	530.000	0.010	2.000	0.500	0.770	0.563	0.414	1.793	SimpleImputer()	None	CustomOrdinalEncoder()
21	0.763	0.741	0.785	20.000	500.000	0.010	1.000	0.741	0.500	0.500	0.000	4.000	SimpleImputer()	PCA('mle')	OneHotEncoder()
22	0.763	0.743	0.783	10.000	500.000	0.010	1.000	0.720	1.000	0.576	1.000	3.797	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
23	0.762	0.741	0.784	11.000	536.000	0.013	2.000	0.661	0.525	0.683	0.063	2.415	SimpleImputer(strategy='median')	None	OneHotEncoder()
24	0.761	0.736	0.787	20.000	500.000	0.010	2.000	0.796	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
25	0.761	0.737	0.785	20.000	500.000	0.010	1.000	0.500	1.000	0.747	0.000	1.000	SimpleImputer()	None	OneHotEncoder()
26	0.759	0.735	0.784	20.000	500.000	0.010	1.000	0.500	0.762	1.000	0.000	1.000	SimpleImputer()	None	CustomOrdinalEncoder()
27	0.757	0.734	0.780	3.000	500.000	0.010	1.000	0.795	0.578	0.641	1.000	1.528	SimpleImputer(strategy='median')	PCA('mle')	CustomOrdinalEncoder()
28	0.757	0.735	0.779	1.000	2,000.000	0.010	1.000	0.778	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
29	0.757	0.735	0.779	20.000	500.000	0.010	4.000	0.500	0.952	0.695	1.000	4.000	SimpleImputer(strategy='median')	PCA('mle')	OneHotEncoder()
30	0.757	0.736	0.777	1.000	2,000.000	0.010	6.000	0.640	0.500	0.500	0.003	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
31	0.755	0.730	0.779	1.000	779.000	0.010	3.000	0.500	0.874	0.509	0.003	2.278	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
32	0.755	0.732	0.777	2.000	660.000	0.010	8.000	0.677	0.501	0.926	0.000	1.037	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
33	0.753	0.733	0.774	20.000	2,000.000	0.010	1.000	0.500	0.500	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
34	0.753	0.726	0.779	1.000	500.000	0.010	1.000	0.500	0.500	1.000	0.000	1.000	SimpleImputer()	None	OneHotEncoder()
35	0.751	0.729	0.772	1.000	2,000.000	0.010	1.000	1.000	0.500	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
36	0.751	0.727	0.774	20.000	500.000	0.010	8.000	0.650	0.805	0.500	1.000	1.150	SimpleImputer(strategy='most_frequent')	PCA('mle')	CustomOrdinalEncoder()
37	0.750	0.729	0.772	5.000	2,000.000	0.010	12.000	0.755	0.500	0.817	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
38	0.748	0.727	0.769	20.000	515.000	0.010	15.000	0.702	1.000	1.000	1.000	1.000	SimpleImputer(strategy='median')	PCA('mle')	OneHotEncoder()
39	0.747	0.723	0.772	20.000	582.000	0.016	3.000	0.500	0.903	0.505	0.000	1.061	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
40	0.747	0.725	0.768	20.000	1,434.000	0.012	1.000	0.746	0.842	0.656	0.000	2.214	SimpleImputer()	None	OneHotEncoder()
41	0.747	0.723	0.771	1.000	500.000	0.010	1.000	0.500	0.579	0.562	1.000	2.486	SimpleImputer()	PCA('mle')	CustomOrdinalEncoder()
42	0.747	0.721	0.772	20.000	2,000.000	0.010	24.000	1.000	0.880	0.500	1.000	1.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
43	0.746	0.726	0.767	5.000	1,130.000	0.014	7.000	0.513	0.885	0.899	0.360	1.495	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
44	0.745	0.726	0.763	20.000	2,000.000	0.010	3.000	0.500	0.500	1.000	1.000	4.000	SimpleImputer()	PCA('mle')	OneHotEncoder()
45	0.744	0.723	0.765	1.000	2,000.000	0.040	12.000	1.000	0.500	0.833	0.633	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
46	0.744	0.723	0.764	1.000	500.000	0.010	10.000	0.525	0.500	1.000	0.102	4.000	SimpleImputer()	PCA('mle')	OneHotEncoder()
47	0.743	0.717	0.769	1.000	500.000	0.010	1.000	0.753	0.605	0.501	1.000	1.993	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
48	0.742	0.718	0.765	20.000	2,000.000	0.010	1.000	0.984	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
49	0.741	0.718	0.763	20.000	2,000.000	0.010	1.000	0.856	1.000	1.000	1.000	1.648	SimpleImputer()	None	OneHotEncoder()
50	0.741	0.715	0.766	1.000	500.000	0.010	3.000	0.831	0.519	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
51	0.739	0.719	0.759	20.000	599.000	0.011	1.000	1.000	1.000	0.838	0.000	4.000	SimpleImputer(strategy='most_frequent')	PCA('mle')	OneHotEncoder()
52	0.738	0.715	0.762	10.000	1,519.000	0.018	11.000	0.527	0.546	0.947	0.000	2.109	SimpleImputer(strategy='median')	PCA('mle')	OneHotEncoder()
53	0.738	0.718	0.758	20.000	2,000.000	0.010	2.000	0.826	1.000	1.000	0.000	3.104	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
54	0.736	0.707	0.765	20.000	500.000	0.010	20.000	1.000	1.000	0.639	0.003	4.000	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
55	0.734	0.712	0.757	20.000	2,000.000	0.010	6.000	0.892	1.000	0.500	0.000	4.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
56	0.734	0.714	0.754	20.000	1,005.000	0.010	2.000	1.000	0.801	0.682	0.208	1.000	SimpleImputer()	PCA('mle')	OneHotEncoder()
57	0.733	0.711	0.755	10.000	1,267.000	0.022	33.000	0.985	0.644	0.850	0.864	3.999	SimpleImputer(strategy='median')	None	OneHotEncoder()
58	0.731	0.706	0.756	1.000	500.000	0.010	1.000	1.000	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
59	0.729	0.705	0.752	20.000	2,000.000	0.010	50.000	1.000	1.000	0.500	1.000	4.000	SimpleImputer(strategy='most_frequent')	None	CustomOrdinalEncoder()
60	0.728	0.707	0.749	20.000	1,208.000	0.300	1.000	0.879	1.000	1.000	1.000	2.751	SimpleImputer(strategy='most_frequent')	None	OneHotEncoder()
61	0.728	0.706	0.750	20.000	1,411.000	0.012	1.000	1.000	0.500	0.545	0.000	2.614	SimpleImputer(strategy='median')	PCA('mle')	CustomOrdinalEncoder()
62	0.727	0.703	0.751	20.000	2,000.000	0.020	1.000	0.617	0.948	0.883	0.000	2.928	SimpleImputer(strategy='most_frequent')	PCA('mle')	CustomOrdinalEncoder()
63	0.725	0.700	0.749	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	<NA>	SimpleImputer()	None	OneHotEncoder()
64	0.723	0.702	0.745	8.000	862.000	0.046	4.000	0.758	0.936	0.930	0.437	1.861	SimpleImputer()	None	OneHotEncoder()
65	0.719	0.699	0.739	20.000	500.000	0.300	50.000	1.000	0.642	0.738	0.000	3.218	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
66	0.717	0.696	0.738	9.000	1,581.000	0.052	8.000	0.985	0.913	0.626	0.013	1.419	SimpleImputer()	PCA('mle')	OneHotEncoder()
67	0.706	0.680	0.733	2.000	1,866.000	0.064	15.000	0.546	0.796	0.885	0.034	2.370	SimpleImputer(strategy='median')	PCA('mle')	OneHotEncoder()
68	0.706	0.690	0.723	17.000	1,332.000	0.298	1.000	0.507	0.790	0.512	0.003	1.642	SimpleImputer()	PCA('mle')	OneHotEncoder()
69	0.706	0.684	0.728	2.000	1,352.000	0.067	10.000	0.952	0.516	0.591	0.061	1.080	SimpleImputer(strategy='median')	PCA('mle')	CustomOrdinalEncoder()
70	0.703	0.680	0.726	15.000	1,670.000	0.209	17.000	0.637	0.984	0.537	0.000	2.331	SimpleImputer(strategy='median')	None	OneHotEncoder()
71	0.701	0.675	0.727	3.000	1,618.000	0.132	3.000	0.691	0.993	0.911	0.054	1.880	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()
72	0.695	0.669	0.721	1.000	500.000	0.010	50.000	1.000	1.000	0.789	0.020	2.377	SimpleImputer(strategy='median')	None	OneHotEncoder()
73	0.693	0.670	0.716	9.000	1,131.000	0.258	6.000	0.911	0.921	0.826	0.003	2.131	SimpleImputer()	PCA('mle')	CustomOrdinalEncoder()
74	0.685	0.665	0.706	1.000	1,705.000	0.233	28.000	0.849	0.616	0.603	0.000	1.856	SimpleImputer()	PCA('mle')	CustomOrdinalEncoder()
75	0.685	0.660	0.710	15.000	868.000	0.010	26.000	0.516	0.850	0.976	0.535	1.698	SimpleImputer(strategy='median')	PCA('mle')	OneHotEncoder()
76	0.500	<NA>	<NA>	20.000	1,914.000	0.028	50.000	0.500	0.731	0.626	0.001	1.956	SimpleImputer(strategy='median')	None	CustomOrdinalEncoder()

results.to_formatted_dataframe(query='model == "LogisticRegression()"', num_rows=60, include_rank=True)

rank	roc_auc Mean	roc_auc 95CI.LO	roc_auc 95CI.HI	C	imputer	scaler	pca	encoder
1	0.771	0.751	0.791	0.055	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
2	0.771	0.750	0.791	0.049	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
3	0.771	0.751	0.791	0.062	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
4	0.770	0.750	0.791	0.077	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
5	0.770	0.750	0.791	0.075	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
6	0.770	0.750	0.791	0.075	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
7	0.770	0.750	0.791	0.075	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
8	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
9	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
10	0.770	0.750	0.791	0.075	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
11	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
12	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
13	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
14	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
15	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
16	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
17	0.770	0.750	0.791	0.089	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
18	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
19	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
20	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
21	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
22	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
23	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
24	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
25	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
26	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
27	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
28	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
29	0.770	0.750	0.791	0.073	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
30	0.770	0.750	0.791	0.073	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
31	0.770	0.750	0.791	0.074	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
32	0.770	0.750	0.791	0.087	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
33	0.770	0.750	0.790	0.092	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
34	0.770	0.750	0.790	0.067	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
35	0.769	0.749	0.790	0.121	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
36	0.769	0.749	0.789	0.097	SimpleImputer(strategy='median')	StandardScaler()	PCA('mle')	OneHotEncoder()
37	0.768	0.748	0.788	0.132	SimpleImputer(strategy='median')	StandardScaler()	None	OneHotEncoder()
38	0.764	0.734	0.795	0.054	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
39	0.764	0.735	0.793	0.125	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
40	0.763	0.736	0.790	0.281	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
41	0.763	0.733	0.793	0.031	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
42	0.762	0.732	0.792	0.023	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
43	0.760	0.730	0.790	0.012	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
44	0.758	0.736	0.781	0.897	SimpleImputer()	MinMaxScaler()	None	OneHotEncoder()
45	0.758	0.735	0.781	0.007	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()
46	0.758	0.739	0.777	1.209	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
47	0.757	0.738	0.777	<NA>	SimpleImputer()	StandardScaler()	None	OneHotEncoder()
48	0.756	0.727	0.784	0.001	SimpleImputer(strategy='median')	MinMaxScaler()	None	OneHotEncoder()
49	0.755	0.727	0.784	0.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
50	0.755	0.727	0.784	0.000	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
51	0.755	0.727	0.784	0.000	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
52	0.755	0.727	0.784	0.000	SimpleImputer()	MinMaxScaler()	PCA('mle')	OneHotEncoder()
53	0.751	0.732	0.769	4.732	SimpleImputer(strategy='most_frequent')	MinMaxScaler()	None	OneHotEncoder()
54	0.745	0.727	0.762	98.285	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	OneHotEncoder()
55	0.745	0.728	0.762	23.327	SimpleImputer(strategy='median')	StandardScaler()	None	OneHotEncoder()
56	0.744	0.726	0.762	100.000	SimpleImputer(strategy='median')	MinMaxScaler()	PCA('mle')	OneHotEncoder()
57	0.735	0.706	0.765	0.001	SimpleImputer()	StandardScaler()	PCA('mle')	OneHotEncoder()
58	0.731	0.713	0.750	0.027	SimpleImputer()	StandardScaler()	None	CustomOrdinalEncoder()
59	0.731	0.712	0.749	0.004	SimpleImputer(strategy='most_frequent')	StandardScaler()	PCA('mle')	CustomOrdinalEncoder()
60	0.730	0.699	0.761	0.000	SimpleImputer(strategy='most_frequent')	StandardScaler()	None	OneHotEncoder()

BayesSearchCV Performance Over Time

results.plot_performance_across_trials(facet_by='model').show()

results.plot_performance_across_trials(query='model == "XGBClassifier()"').show()

---

Variable Performance Over Time

results.plot_parameter_values_across_trials(query='model == "XGBClassifier()"').show()

---

Scatter Matrix

# results.plot_scatter_matrix(query='model == "XGBClassifier()"',
#                             height=1000, width=1000).show()

---

Variable Performance - Numeric

results.plot_performance_numeric_params(query='model == "XGBClassifier()"',
                                        height=800)

/Users/shanekercheval/opt/anaconda3/envs/python-examples/lib/python3.9/site-packages/statsmodels/nonparametric/smoothers_lowess.py:227: RuntimeWarning:

invalid value encountered in true_divide

results.plot_parallel_coordinates(query='model == "XGBClassifier()"').show()

---

Variable Performance - Non-Numeric

results.plot_performance_non_numeric_params(query='model == "XGBClassifier()"').show()

---

results.plot_score_vs_parameter(
    query='model == "XGBClassifier()"',
    parameter='learning_rate',
    size='colsample_bytree',
    color='encoder',
)

---

results.plot_parameter_vs_parameter(
    query='model == "XGBClassifier()"',
    parameter_x='colsample_bytree',
    parameter_y='learning_rate',
    size='max_depth'
)

results.plot_parameter_vs_parameter(
    query='model == "XGBClassifier()"',
    parameter_x='colsample_bytree',
    parameter_y='learning_rate',
    size='imputer'
)